How Google’s PageRank predicts Nobel Prize winners

Ranking scientists by their citations–the number of times they are mentioned in other scientists’ papers– is a miserable business. Everybody can point to ways in which this system is flawed:

not all citations are equal. The importance of the citing paper is a significant factor

scientists in different fields of study use citations in different ways. An average paper in the life sciences is cited about six times, three times in physics, and about once in mathematics.

ground-breaking papers may be cited less often because a field is necessarily smaller in its early days.

important papers often stop being cited when they are incorporated into textbooks

The pattern of citations between papers forms a complex network, not unlike the one the internet forms. Might that be a clue that point us towards a better way of assessing the merits of the papers that it consists of?

Sergei Maslov from Brookhaven National Laboratory in New York state and Sidney Redner at Boston University have asked themselves just that question and suggest that Google’s PageRank algorithm might throw some light on the matter.

In essence, PageRank counts the number of citations a paper receives (or the number of links that point to a webpage). The more a paper receives, the higher it is ranked. But a citing is also weighted according to the ranking of the citing paper. So citations from important papers make another paper more important.

Maslov and Redner have applied the algorithm to 353,268 articles published by the American Physical Society since 1893 in journals such as Physical Review Letters . And the results are a breath of fresh air.

The top 10 papers by Google Pageranking are:

Unitary Symmetry & Leptonic Decays by Cabibbo

Theory of Superconductivity by Bardeen, Cooper & Schrieffer

Self-Consistent Equations . . . by Kohn & Sham

Inhomogeneous Electron Gas by Hohenberg & Kohn

A Model of Leptons by Weinberg

Crystal Statistics . . . by Onsager

Theory of the Fermi Interaction by Feynman & Gell-Mann

Absence of Diffusion in . . . by Anderson

The Theory of Complex Spectra by Slater

Scaling Theory of Localization by Abrahams, Anderson, et al.

That’s an impressive list, not least because most of these authors are Nobel Prize winners. (Curiously the author of the top paper, Nicola Cabibbo, is not. That ought to be of interest to the Nobel committee who awarded Makoto Kobayashi and Toshihide Maskawa the 2008 Nobel Prize for physics for work that was heavily based on Cabibbo’s ideas.)

All of which suggests an idea. Mining the later entries in this list might be an good way of predicting future prize winners. So get your bets in before the bookies get wind of it.

Redner and Maslov conclude: “Google’s PageRank algorithm and its modifications hold great promise for quantifying the impact of scientific publications.”

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[...] analyze citation graphs in academic publishing. I’ll refrain from summarizing the paper, as a related post on the arXiv physics blog has already done a great job on that. But the upshot is that [...]

I agree with anon and andri – scientists will be attracted to areas of research that have awarded Nobel prizes, as these are seen as topics of significance and fertile regions for further discoveries. Consequently, more researchers will cite papers by Nobel authors – so there is cause and effect, it’s just that Maslov and Redner have mistaken one for the other.

[...] from the list: number 1 ranked Nicola Cabibbo. Perhaps this year’s his year. (Hat tip: the physics arXiv blog) Bookmark and Share These icons link to social bookmarking sites where readers can share and [...]

Unlike Reow, I believe scientists who focus on areas of research that have been awarded Nobel prizes, may ruin their careers. Those areas were perhaps topics of significance and fertile regions for further discoveries, but that was a decade or decades ago and probably have lost its prime significance.

I think this issue is very important, because this measures are used to decide the career of researchers and the funding of institutions.
Receiving a nobel is for sure a measure of quality for the research produced, but it’s a bit too sparse to indicate if a ranking method is effective.
I would like to see this page ranking method used as a predictor of future production. For example a cumulative page rank for an author computed at a certain point in time (with all the citations until that time) could be correlated with the future page rank, or the future number of citations, or the future number of papers produced. And then I would like to see this compared with the other quality measures, such as citation index or impact factor.

[...] the American Physical Society since 1893 (abstract). The results make interesting reading because almost all of the top ten papers resulted in (or were linked to) Nobel Prizes for their authors. Which means that studying the up-and-coming entries on the list ought to be a good way of [...]

[...] How Google’s PageRank predicts Nobel Prize winners "In essence, PageRank counts the number of citations a paper receives (or the number of links that point to a webpage). The more a paper receives, the higher it is ranked. But a citing is also weighted according to the ranking of the citing paper. So citations from important papers make another paper more important." (Tags: via:mento.info citation research pagerank science polkarobot) [...]